Safety infrastructure for healthcare AI
Your safety evidence expires every time your model changes.
Independent, clinician-calibrated evaluation for AI in healthcare. Sesh stress-tests your agent the way your hardest patients do, grades what it said, and hands you the evidence — on a cadence, not once.
Nobody accepts a self-graded safety report.
You can write your own test cases. You can’t credibly grade yourself — and everyone who eventually asks (a regulator, an insurer, a certification reviewer, a procurement team) wants an assessment from someone with no stake in the answer.
Not a prompt on a foundation model
Every part of Sesh is custom-built for clinical risk — an attacker, a judge, and a guard, engineered for the job rather than a foundation model steered with a system prompt.
A purpose-built attacker
Built to probe your agent like your hardest patients do — the disclosures that arrive sideways, the risk that hides in a reasonable tone. Generic red-teaming walks past it.
A calibrated judge
Measured against clinician-defined ground truth, so it weighs what actually matters in care: did it notice the risk, escalate at the right threshold, avoid false reassurance. Not a foundation model asked to grade itself.
A runtime guard
Watches live conversations and escalates real risk the moment it appears — without standing between a patient and help.
What you get
- A delta report — exactly what your current safety layer is missing, before anything reaches a patient.
- Evidence on a cadence — the recurring score card your board, insurer, and certification reviewer will actually read.
- Regression-proof CI — safety re-runs on every model or prompt change, and blocks the ones that fail.
Who builds it
A decade of AI in healthcare — ML lead at Headspace Health, research at NYU Langone and Northwell — and an NBC-HWC certified coach who has sat with clients. In clinical safety, the clinical judgment is the scarce half. It’s the half this is built from.
See what your safety layer is missing.
A scoped evaluation against your live agent — you see what we found before anything changes.